Eve H. Pickering

2.5k total citations
29 papers, 1.6k citations indexed

About

Eve H. Pickering is a scholar working on Physiology, Molecular Biology and Genetics. According to data from OpenAlex, Eve H. Pickering has authored 29 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Physiology, 13 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Eve H. Pickering's work include Alzheimer's disease research and treatments (10 papers), Genetic Associations and Epidemiology (4 papers) and Dementia and Cognitive Impairment Research (3 papers). Eve H. Pickering is often cited by papers focused on Alzheimer's disease research and treatments (10 papers), Genetic Associations and Epidemiology (4 papers) and Dementia and Cognitive Impairment Research (3 papers). Eve H. Pickering collaborates with scholars based in United States, Singapore and United Kingdom. Eve H. Pickering's co-authors include Kelly R. Bales, David M. Holtzman, Anne M. Fagan, Holly Soares, Bryan Dechairo, John C. Morris, Alison Goate, Carlos Cruchaga, Sarah Bertelsen and Linda S. Wood and has published in prestigious journals such as PLoS ONE, Biological Psychiatry and CHEST Journal.

In The Last Decade

Eve H. Pickering

29 papers receiving 1.5k citations

Peers

Eve H. Pickering
Lena Kilander Sweden
Nobuto Shibata Japan
Tim West United States
Étienne Croteau Canada
Rebecca Sims United Kingdom
Jianfang Ma China
Albert Hofman Netherlands
Anna M. Barron Singapore
M. Florencia Iulita Canada
Jennifer R. Cracchiolo United States
Lena Kilander Sweden
Eve H. Pickering
Citations per year, relative to Eve H. Pickering Eve H. Pickering (= 1×) peers Lena Kilander

Countries citing papers authored by Eve H. Pickering

Since Specialization
Citations

This map shows the geographic impact of Eve H. Pickering's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eve H. Pickering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eve H. Pickering more than expected).

Fields of papers citing papers by Eve H. Pickering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eve H. Pickering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eve H. Pickering. The network helps show where Eve H. Pickering may publish in the future.

Co-authorship network of co-authors of Eve H. Pickering

This figure shows the co-authorship network connecting the top 25 collaborators of Eve H. Pickering. A scholar is included among the top collaborators of Eve H. Pickering based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eve H. Pickering. Eve H. Pickering is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Deming, Yuetiva, Jian Xia, Yefei Cai, et al.. (2015). A potential endophenotype for Alzheimer's disease: cerebrospinal fluid clusterin. Neurobiology of Aging. 37. 208.e1–208.e9. 48 indexed citations
2.
Harari, Oscar, Carlos Cruchaga, John S. K. Kauwe, et al.. (2014). Phosphorylated Tau-Aβ42 Ratio as a Continuous Trait for Biomarker Discovery for Early-Stage Alzheimer’s Disease in Multiplex Immunoassay Panels of Cerebrospinal Fluid. Biological Psychiatry. 75(9). 723–731. 69 indexed citations
3.
Kauwe, John S. K., Matthew H. Bailey, Perry G. Ridge, et al.. (2014). Genome-Wide Association Study of CSF Levels of 59 Alzheimer's Disease Candidate Proteins: Significant Associations with Proteins Involved in Amyloid Processing and Inflammation. PLoS Genetics. 10(10). e1004758–e1004758. 98 indexed citations
4.
Fava, Maurizio, et al.. (2014). A Randomized, Double-Blind, Placebo-Controlled Phase 2 Study of the Augmentation of a Nicotinic Acetylcholine Receptor Partial Agonist in Depression. Journal of Clinical Psychopharmacology. 35(1). 51–56. 14 indexed citations
5.
Zhu, Hongjie, Mikhail B. Bogdanov, Stephen H. Boyle, et al.. (2013). Pharmacometabolomics of Response to Sertraline and to Placebo in Major Depressive Disorder – Possible Role for Methoxyindole Pathway. PLoS ONE. 8(7). e68283–e68283. 70 indexed citations
6.
Kaddurah‐Daouk, Rima, Mikhail B. Bogdanov, William R. Wikoff, et al.. (2013). Pharmacometabolomic mapping of early biochemical changes induced by sertraline and placebo. Translational Psychiatry. 3(1). e223–e223. 74 indexed citations
7.
Kauwe, John, Matthew H. Bailey, Perry G. Ridge, et al.. (2013). O4–01–01: Association of genetic variants with cerebrospinal fluid protein levels of ACE, MMP3 and other proteins and risk for Alzheimer's disease. Alzheimer s & Dementia. 9(4S_Part_17). 1 indexed citations
8.
Huang, Jing-Feng, Yi Zhang, Kay D. Rittenhouse, Eve H. Pickering, & Michael T. McDowell. (2012). Evaluations of Tear Protein Markers in Dry Eye Disease: Repeatability of Measurement and Correlation with Disease. Investigative Ophthalmology & Visual Science. 53(8). 4556–4556. 51 indexed citations
9.
10.
Cruchaga, Carlos, John S. K. Kauwe, Petra Nowotny, et al.. (2012). Cerebrospinal fluid APOE levels: an endophenotype for genetic studies for Alzheimer's disease. Human Molecular Genetics. 21(20). 4558–4571. 157 indexed citations
11.
Peterson, Barry T., Ping Chiao, Eve H. Pickering, et al.. (2012). Comparison of actigraphy and polysomnography to assess effects of zolpidem in a clinical research unit. Sleep Medicine. 13(4). 419–424. 34 indexed citations
12.
13.
Huang, Jing-Feng, Min Zhang, Michael T. McDowell, et al.. (2012). Immunomodulatory Effect of the Topical Ophthalmic Janus Kinase Inhibitor Tofacitinib (CP-690,550) in Patients with Dry Eye Disease. Ophthalmology. 119(7). e43–e50. 62 indexed citations
14.
Kaddurah‐Daouk, Rima, Wayne R. Matson, Swati Sharma, et al.. (2011). Pretreatment metabotype as a predictor of response to sertraline or placebo in depressed outpatients: a proof of concept. Translational Psychiatry. 1(7). e26–e26. 102 indexed citations
15.
Hu, Xiaolan, Eve H. Pickering, Sara Hall, et al.. (2011). Genome-wide association study identifies multiple novel loci associated with disease progression in subjects with mild cognitive impairment. Translational Psychiatry. 1(11). e54–e54. 30 indexed citations
16.
Hu, Xiaolan, Eve H. Pickering, Hélène Fournier, et al.. (2011). Meta-Analysis for Genome-Wide Association Study Identifies Multiple Variants at the BIN1 Locus Associated with Late-Onset Alzheimer's Disease. PLoS ONE. 6(2). e16616–e16616. 124 indexed citations
17.
Hu, William T., Alice Chen‐Plotkin, Steven E. Arnold, et al.. (2010). Novel CSF biomarkers for Alzheimer’s disease and mild cognitive impairment. Acta Neuropathologica. 119(6). 669–678. 150 indexed citations
18.
Wood, Linda S., Eve H. Pickering, Duncan P. McHale, & Bryan Dechairo. (2007). Association between neprilysin polymorphisms and sporadic Alzheimer's disease. Neuroscience Letters. 427(2). 103–106. 21 indexed citations
19.
Jensen, Robert L., et al.. (2007). Sources of Long-term Variability in Measurements of Lung Function. CHEST Journal. 132(2). 396–402. 41 indexed citations
20.
Thompson, John F., Linda S. Wood, Eve H. Pickering, Bryan Dechairo, & Craig Hyde. (2006). High-density genotyping and functional SNP localization in the CETP gene. Journal of Lipid Research. 48(2). 434–443. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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